MetaTrader 5 Machine Learning Blueprint – Modules Repository

This repository contains the companion code modules, utilities, and assets for the MetaTrader 5 Machine Learning Blueprint article series by Patrick Murimi Njoroge.
It is designed to be a clean, production‑ready implementation of advanced financial machine learning techniques — from robust data handling to adaptive, probabilistic trade execution.

---

📚 Series Context

This repo accompanies the following articles:

1. Part 1 – Data Integrity & Tick‑Based Bars

   • Eliminating data leakage with proper tick aggregation
   • Timestamp correction and unbiased dataset preparation

2. Part 2 – Meta‑Labeling & Triple‑Barrier Method

   • Risk‑aware labeling with profit‑taking/stop‑loss logic
   • Meta‑labels to improve classifier precision under realistic trading constraints

3. Part 3 – Advanced Labeling & Sample Weighting

   • Trend‑scanning labels with adaptive horizons
   • Purged cross‑validation
   • Sample weighting to address concurrency bias
   • Probabilistic position sizing for real‑time execution

---

🔑 Key Features

• Leakage‑Proof Labeling – Triple‑barrier & adaptive trend‑scanning with volatility regime filtering

• Numba‑Accelerated – 100×–350× faster execution for live‑trading scenarios

• Concurrency‑Aware Weighting – Down‑weights overlapping observations for better generalization

• Probabilistic Position Sizing – Trade sizing aligned with model confidence and risk parameters

• MT5 Integration – Direct pipeline from Python model output to MetaTrader 5 execution